AI Specialist

Job Description

Coursera is seeking an AI Specialist to develop and deploy advanced AI solutions. The ideal candidate will have 3+ years of experience in leveraging AI technologies to derive insights, build predictive models, and enhance platform capabilities. This role offers a unique opportunity to contribute to cutting-edge projects that transform the online learning experience.

Responsibilities:

• Deploy and customize AI/ML solutions using tools and platforms from Google AI, AWS, or other providers.
• Develop and optimize customer journey analytics to identify actionable insights and improve user experience.
• Design, implement, and optimize models for predictive analytics, information extraction, semantic parsing, and topic modelling.
• Perform comprehensive data cleaning and preprocessing to ensure high-quality inputs for model training and deployment.
• Build, maintain, and refine AI pipelines for data gathering, curation, model training, evaluation, and monitoring.
• Analyze large-scale datasets, including customer reviews, to derive insights for improving recommendation systems and platform features.
• Train and support team members in adopting and managing AI-driven tools and processes.
• Document solutions, workflows, and troubleshooting processes to ensure knowledge continuity.
• Stay informed on emerging AI/ML technologies to recommend suitable solutions for new use cases.
• Evaluate and enhance the quality of video and audio content using AI-driven techniques.

Requirements:

• Bachelor's degree in Computer Science, Machine Learning, or a related field (required).
• 3+ years of experience in AI/ML development, with a focus on predictive modelling and data-driven insights.
• Proven experience in deploying AI solutions using platforms like Google AI, AWS, Microsoft Azure, or similar.
• Proficiency in programming languages such as Python, Java, or similar for AI tool customization and deployment.
• Strong understanding of APIs, cloud services, and integration of AI tools with existing systems.
• Proficiency in building and scaling AI pipelines for data engineering, model training, and monitoring.
• Experience with frameworks and libraries for building AI agents, such as LangChain, AutoGen
• Familiarity with designing autonomous workflows using LLMs and external APIs
• Advanced proficiency in Python, PyTorch, and TensorFlow, SciKit-Learn
• Expertise in data cleaning, preprocessing, and handling large-scale datasets. Preferred experience with tools like AWS Glue, PySpark, and AWS S3.
• Experience with AWS SageMaker, Google AI, Google Vertex AI, Databricks
• Strong SQL skills and advanced proficiency in statistical programming languages such as Python, along with experience using data manipulation libraries (e.g., Pandas, NumPy).

Coursera Offers:

• Flexibility and workspace choices for employees.
• Remote work options.